AMR Country Hotspots

##  Family: zero_inflated_poisson 
##   Links: mu = log; zi = logit 
## Formula: n_amr_events ~ ln_livestock_consumption_kg_per_capita + ln_migrant_pop_perc + ln_tourism_inbound_perc + ln_tourism_outbound_perc + ab_export_perc + health_expend_perc + human_consumption_ddd + english_spoken + ln_pubs_sum_per_capita + ln_promed_mentions_per_capita + ln_gdp_per_capita + offset(ln_population) 
##          zi ~ ln_pubs_sum_per_capita + ln_promed_mentions_per_capita + ln_gdp_per_capita + ln_population + english_spoken
##    Data: data[[i]] (Number of observations: 198) 
## Samples: 120 chains, each with iter = 2000; warmup = 1000; thin = 1;
##          total post-warmup samples = 120000
## 
## Population-Level Effects: 
##                                        Estimate Est.Error l-95% CI
## Intercept                                -13.27      3.22   -19.87
## zi_Intercept                              29.52      6.99    16.52
## ln_livestock_consumption_kg_per_capita    -0.35      0.16    -0.57
## ln_migrant_pop_perc                        0.23      0.05     0.10
## ln_tourism_inbound_perc                    0.11      0.11    -0.08
## ln_tourism_outbound_perc                   0.03      0.19    -0.40
## ab_export_perc                             5.26      1.25     2.55
## health_expend_perc                         0.02      0.03    -0.06
## human_consumption_ddd                      0.09      0.02     0.05
## english_spoken                            -0.58      0.17    -0.89
## ln_pubs_sum_per_capita                     0.11      0.13    -0.15
## ln_promed_mentions_per_capita              0.26      0.09     0.10
## ln_gdp_per_capita                         -0.09      0.10    -0.29
## zi_ln_pubs_sum_per_capita                 -0.07      0.29    -0.65
## zi_ln_promed_mentions_per_capita           0.16      0.35    -0.50
## zi_ln_gdp_per_capita                      -1.34      0.30    -1.97
## zi_ln_population                          -1.01      0.23    -1.49
## zi_english_spoken                         -1.51      0.66    -2.87
##                                        u-95% CI Eff.Sample Rhat
## Intercept                                 -7.24         76 2.18
## zi_Intercept                              43.99       2562 1.02
## ln_livestock_consumption_kg_per_capita    -0.01         63 4.54
## ln_migrant_pop_perc                        0.33         86 1.82
## ln_tourism_inbound_perc                    0.35         67 3.21
## ln_tourism_outbound_perc                   0.35         65 3.65
## ab_export_perc                             7.44        105 1.53
## health_expend_perc                         0.09         75 2.24
## human_consumption_ddd                      0.13         72 2.46
## english_spoken                            -0.09         72 2.50
## ln_pubs_sum_per_capita                     0.36         92 1.70
## ln_promed_mentions_per_capita              0.42         80 1.99
## ln_gdp_per_capita                          0.13         90 1.73
## zi_ln_pubs_sum_per_capita                  0.49       1135 1.03
## zi_ln_promed_mentions_per_capita           0.86       4303 1.01
## zi_ln_gdp_per_capita                      -0.78       1756 1.02
## zi_ln_population                          -0.58       1699 1.02
## zi_english_spoken                         -0.26        801 1.04
## 
## Samples were drawn using sampling(NUTS). For each parameter, Eff.Sample 
## is a crude measure of effective sample size, and Rhat is the potential 
## scale reduction factor on split chains (at convergence, Rhat = 1).

## [1] TRUE